초록

Face replacement system plays an important role in the entertainment industries. However, most of these systems nowadays are assisted by hand and specific tools. In this paper, a new face replacement system for automatically replacing a face with image processing technique is described. The system is divided into two main parts: facial feature extraction and face pose estimation. In the first part, the face region is determined and the facial features are extracted and located. Eyes, mouth, and chin curve are extracted by their statistical and geometrical properties. These facial features are used as the information for the second part. A neural network is adopted here to classify the face pose according to the feature vectors which are obtained from the different ratio of facial features. From the experiments and some comparisons, they show that this system works better while dealing with different pose, especially for non-frontal face pose.